volatility spillover

  • 详情 High-Low Volatility Spillover Network in Chinese Financial Market from a Multiscale Perspective
    Based on the formation and evolution of systemic risk, this study proposes high and low volatility spillover networks and explores the characteristics of the evolution of systemic risk in Chinese financial market, and identifies the source of risk accumulation and risk outbreak, as well as the corresponding contagion mechanisms. Moreover, a new multiscale decomposition method (MVMD) is used to decompose high and low volatility into different time frequency components (short-term and long-term), and the corresponding network is constructed. Upon comparing topological characteristics on each layer from system and individual levels, our results reveal that high and low volatility spillover networks have different network characteristics and evolution behaviors. At the individual level, bond market is always the largest risk net-receivers in the high and low volatility networks, while the futures market and the currency market are respectively risk net-emitters in the high and low volatility networks. Additionally, compared with high volatility network, the low volatility network has greater predictive ability for financial risk. Finally, frequency analysis demonstrates that high-low volatility networks have different spillover intensity and network structure at different time frequencies. The above findings are beneficial for policy makers and investors to formulate appropriate strategies in different evolution of systemic risk and time frequency.
  • 详情 COVID-19, ‘Meteor Showers’ and the Dependence Structure Among Major Developed and Emerging Stock Markets
    This paper investigates the impact of the COVID-19 pandemic on the volatility spillover and dependence structure among the major developed and emerging stock markets. The TVP-VAR connectedness decomposition approach and R-vine copula are implemented in this research. The results of the TVP-VAR connectedness decomposition approach reveal that the volatility spillover among the major developed and emerging stock markets has been significantly strengthened by the outbreak of the COVID-19 pandemic, although it has gradually faded over time. In addition, during the pandemic, the UK, German, French and Canadian stock markets are the spillover transmitters, while the Japanese, Chinese Hong Kong, Chinese and Indian stock markets are the receivers. It is also found that the US and Brazilian stock markets have undergone role shifts after the outbreak of the COVID-19 pandemic. The results of the R-vine copula model indicate that during the pandemic, the Canadian, French, and Chinese Hong Kong stock markets are the most important financial centre in the American, European, and Asian stock markets, respectively. Furthermore, the effect of the extreme risk contagion has been strengthened by the pandemic, particularly the downside risk contagion.
  • 详情 The Evolving Patterns of the Price Discovery Process: Evidence from the Stock Index Futures Markets of China, India and Russia
    This study examines the price discovery patterns in the three BRICS countries’ stock index futures markets that were launched after 2000 – China, India, and Russia. We detect two structural breaks in these three futures price series and their underlying spot price series, and use them to form subsamples. Employing a Vector Error Correction Model (VECM) and the Hasbrouck (1995) test, we find the price discovery function of stock index futures markets generally improves over time in China and India, but declines in Russia. A closer examination not only confirms the findings of Yang et al. (2012) and Hou and Li (2013) regarding price discovery in China’s stock index markets, but also reveals the inconsistency of futures’ leading role in the price discovery process. Further, we find some evidence of day-of-the-week effects in earlier part of the sample in China, but not in India or Russia. And our GARCH model results show bidirectional volatility spillover between futures and spot in China and India, but only unidirectional in Russia.
  • 详情 Volatility Spillovers from the Chinese Stock Market to Economic Neighbours
    This paper examines whether there is evidence of spillovers of volatility from the Chinese stock market to its neighbours and trading partners, including Australia, Hong Kong, Singapore, Japan and USA. China's increasing integration into the global market may have important consequences for investors in related markets. In order to capture these potential eects, we explore these issues using an Autoregressive Moving Average (ARMA) return equation. A univariate GARCH model is then adopted to test for the persistence of volatility in stock market returns, as represented by stock market indices. Finally, univariate GARCH, multivariate VARMA-GARCH, and multivariate VARMA-AGARCH models are used to test for constant conditional correlations and volatility spillover eects across these markets. Each model is used to calculate the conditional volatility between both the Shenzhen and Shanghai Chinese markets and several other markets around the Pacic Basin Area, including Australia, Hong Kong, Japan, Taiwan and Singapore, during four distinct periods, beginning 27 August 1991 and ending 17 November 2010. The empirical results show some evidence of volatility spillovers across these markets in the pre-GFC periods, but there is little evidence of spillover eects from China to related markets during the GFC. This is presumably because the GFC was initially a US phenomenon, before spreading to developed markets around the globe, so that it was not a Chinese phenomenon.
  • 详情 China’s Stock Market Integration with a Leading Power and a Close Neighbor
    Current integration and co-movement among international stock markets has been boosted by increased globalization of the world economy, and profit-chasing capital surfing across borders. With a reputation as the fastest growing economy in the world, China’s stock market has continued gaining momentum during recent years and incurred growing attention from academicians, as well as practitioners. Taking into account economic and geographical considerations, the US and Hong Kong are considerably the most comparable stock markets to China. As the usual vector error correction model (VECM) could overlook the long memory feature of cointegration residual series, which can in turn exert bias on the resulting inferences, we chose to employ a fractionally integrated VECM (FIVECM) in this paper to investigate the long-term cointegration relations binding China’s stock market to the aforementioned stock markets. In addition, by augmenting the FIVECM with multivariate GARCH model, the return transmission and volatility spillover between market return series were revealed simultaneously. Our empirical results show that China’s stock market is fractionally cointegrated with the two markets, and it appears that China’s stock market has stronger ties with its neighboring Hong Kong market than with the world superpower, the US market.
  • 详情 Stock Volatility in the Segmented Chinese Stock Markets: A SWARCH Approach
    This study adopts the Markov-switching ARCH (hereafter SWARCH) model to examine the volatility nature and volatility linkages of four segmented Chinese stock indices (SHA, SZA, SHB, and SZB). Our empirical findings are consistent with the following notions. First, we find strong evidence of regime shift in the volatility of four segmented markets and SWARCH model appears to outperform standard GARCH family models. Second, although there are some common features of volatility switch in segmented markets, there exist a few difference: (i)compared with the A-share markets, B-share markets are more volatile and shift more frequently between high- and low-volatility states; (ii) B-share markets have longer stays at high volatility state than the A-share markets; (iii) the relative magnitude of the high volatility compared with that of the low volatility is much greater than the case in two A-share markets. Third, B-share markets are found to be more sensitive to international shocks, while the A-share markets seem immune to international spillovers of volatility. Finally, analyses of volatility spillover effect among the four stock markets indicate that the A-share markets play a dominant role in volatility in Chinese stock markets.
  • 详情 Spillovers of the U.S. Subprime Financial Turmoil to Mainland China and Hong Kong Sar: Evidence from Stock Markets
    This paper focuses on evidence from stock markets as it investigates the spillovers from the United States to mainland China and Hong Kong SAR during the subprime crisis. Using both univariate and multivariate GARCH models, this paper finds that China's stock market is not immune to the financial crisis, as evidenced by the price and volatility spillovers from the United States. In addition, HK's equity returns have exhibited more significant price and volatility spillovers from the United States than China's returns, and past volatility shocks in the United States have a more persistent effect on future volatility in HK than in China, reflecting HK's role as an international financial center. Moreover, the impact of the volatility from the United States on China's stock markets has been more persistent than that from HK, due mainly to the United States as the origin of the subprime crisis. Finally, as expected, the conditional correlation between China and HK has outweighed their conditional correlations with the United States, echoing increasing financial integration between China and HK.
  • 详情 Volatility Spillovers between the US and the China Stock Market: Structural Break Test with Symmetric and Asymmetric GARCH Approach
    The paper examines the short-run spillover effect of daily stock returns and volatilities between the S&P 500 in the U.S. and Shanghai SSE composite in China. First, we find that a structural break happened in the SSE stock return mean in December 2005. Second, analyzing modified GARCH (1,1)-M models, we find evidence of a symmetric and asymmetric volatility spillover effect from the U.S. to the China stock market in the post-break period. Third, the symmetric volatility spillover effect from China to the U.S. is also observed in the post-break period.
  • 详情 Spillover Effects between Developed and Emerging Markets with Investment Obstacles: Theory and Empirical Evidence from Copper Futures Markets
    This paper provides a theoretical analysis of return and volatility spillover effects between developed and emerging futures markets with investment obstacles. It mainly focuses on analysis of the effects on equilibrium futures price, investors’ trading strategies and their wealth distributions in the emerging market. Three hypotheses are proposed. The first two assume that there is either return or volatility spillover between the two markets. The last one combines the first two together by assuming that there are both return and volatility spillovers between the markets. Our analysis results show that the equilibrium futures price, investors’ trading strategies and their wealth distributions in the emerging futures market are affected by (1) the scale of informed traders in the emerging market who form their expectations of delivery price by using the spillovers from the developed market, (2) the spillovers degree that the informed in the emerging market expect, and (3) whether there is return spillover or volatility spillover, or both. Overall, the findings suggest that if there are both return and volatility spillovers, then ignoring the volatility spillover, investors will make improper investment decisions so that the futures contracts could be overpriced and the traders’ wealth could be harmed. The theoretical analysis provide an important implication for empirical examination on the spillover effects between markets, that is, both return and volatility spillover effects should be considered jointly, otherwise the return spillover effects can be overestimated. Empirical examination in copper futures markets generally supports the conclusions drawn from our theoretical analysis.